code: def test_hinge_discriminator_adv_loss(self):
      loss_type = "hinge"
      t0 = torch.FloatTensor([0.0, 0.0, 0.0])
      t1 = torch.FloatTensor([1.0, 2.0, 3.0])
  
      assert self._disc_loss(loss_type, t0, t0).item() == 2.0
      assert self._disc_loss(loss_type, t1, t1).item() == 3.0
  
file_path: audiocraft/tests/adversarial/test_losses.py
imports: import pytest
  import random
  import torch
  from audiocraft.adversarial import AdversarialLoss, get_adv_criterion, get_real_criterion, get_fake_criterion, FeatureMatchingLoss, MultiScaleDiscriminator
label_desc: Use image node_id 2 for calling the TestDiscriminatorAdversarialLoss obj's underlying member method code with example usage: obj.test_hinge_discriminator_adv_loss() without return types